The finite-time tracking control problem with the output-constraint property of robotic manipulators subjected to system uncertainties is addressed. Specifically, the radial basis function neural network is employed to compensate for system uncertainties. The finite-time stability theorem is used for the backstepping design process, by which the limit of the settling time is set. A funnel boundary is used to limit the output overshoot. The proposed controller guarantees that all the signals are semi-globally practically finite-time bounded, while the tracking errors are enveloped by the funnel boundary. The performance of the proposed control method is illustrated by a numerical simulation of a 3-DOF manipulator. It is shown that the tracking errors are bounded by prescribed funnel boundaries. In the meantime, the manipulator is stabilized within a finite period of time.

中文翻译：

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具有漏斗边界的机器人机械手的自适应有限时间跟踪控制

解决了受系统不确定性影响的机器人机械手具有输出约束特性的有限时间跟踪控制问题。具体而言，采用径向基函数神经网络来补偿系统的不确定性。有限时间稳定性定理用于反步设计过程，通过该定理设置稳定时间的限制。漏斗边界用于限制输出过冲。所提出的控制器保证所有信号都是半全局的，实际上是有限时间有界的，而跟踪误差则被漏斗边界所包围。所提出的控制方法的性能通过一个 3-DOF 机械手的数值模拟来说明。结果表明，跟踪误差受规定的漏斗边界限制。同时，